bert – AI Model by Noorrabie | AlphaNeural AI

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Noorrabie/
bert

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text-classification

generated_from_trainer

aubmindlab/bert-base-arabertv02

autotrain_compatible

endpoints_compatible

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bert

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.9191
Macro F1: 0.3349
Macro Precision: 0.3782
Macro Recall: 0.3232
Accuracy: 0.4557

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 64
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Macro Precision	Macro Recall	Accuracy
1.8594	1.0	857	1.5842	0.2852	0.3360	0.2880	0.4542
1.3775	2.0	1714	1.5581	0.3394	0.3959	0.3210	0.4575
1.1436	3.0	2571	1.5983	0.3272	0.4183	0.3139	0.4631
0.9682	4.0	3428	1.7181	0.3383	0.3793	0.3254	0.4688
0.7683	5.0	4285	1.8410	0.3318	0.3755	0.3173	0.4535
0.6693	6.0	5142	1.9191	0.3349	0.3782	0.3232	0.4557

Framework versions

Transformers 4.53.0
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2